Research On Track-before-detect Algorithms For Dim Targets On Sea Surface

Detection and tracking of dim and small targets is one of the key problems that modern radar must face.When the target's echo signal energy is very low or the background interference is very strong,the target's echo signal to noise ratio received by the radar sensor is very low.At this time,the traditional detection and tracking method based on single frame threshold decision is difficult to complete the detection and tracking task.The track-before-detect algorithms provides an effective way to solve such problems.This method integrates detection and tracking,does not set a threshold for single frame echo data,and accumulates energy along the possible path of the target.Firstly,the basic theory of track-before-detect algorithms and particle filter is analyzed,and Bayesian theory,Monte Carlo integration and resampling process are introduced.This paper mainly discusses the particle degradation phenomenon in particle filter algorithm,and the commonly used suppression methods,constructing the importance density function and resampling method,are analyzed and compared to provide a theoretical basis for the follow-up work.Secondly,aiming at the degradation of particle filter algorithm,an extended Kalman particle filter algorithm is designed.The posterior probability density of the target,reduce the linear error and enhance the detection and tracking performance of the algorithm.Finally,the track-before-detect algorithm of extended Kalman particle filter is studied.Based on the pre-detection tracking algorithm of particle filter,the track-before-detect algorithms method based on extended Kalman filter and iterative Kalman particle filter is designed.The extended Kalman filter and iterative Kalman filter are introduced into the framework of the track-before-detect algorithms of particle filter.